One of the major problems presently faced by the suppliers of MRI equipment is motion artifacts, particularly in the imaging of the upper thorax and the abdomen. A primary cause of the motion artifacts is motion due to the patient's breathing. Breathing introduces quasi-cyclical changes in the RF data signals received by the MRI system's receiver. The quasi-cyclic nature of the breathing causes a "foreign" frequency to be introduced into the image which multiplies the number of appearances of the lives of the image. Each appearance is slightly displaced from the other appearances. The artifact is known as "ghosting" and appears along the phase encoding axis, lowering the clarity of the image. The ghosts make it difficult to determine lesions in the image. As these quasi-cyclic changes result from non-linear motions along all three axes, to date no software post aquisition processing method has been discovered that is completely effective in correcting the resulting artifacts.
The prior art reveals numerous approaches and methods which have been tried in attempts to minimize the artifacts caused by the breathing of the subject during the MRI process. For example, various post acquisition data processing methods have been tried to reduce the artifacts. Post-processing methods are model dependant. This approach, however, in addition to the aforementioned problem of the three dimensional motion and model dependency inherently requires significantly more time per patient. Since "throughput" is a key requirement of any MRI system, scientists in the field are continually seeking faster alternatives to such time intensive prior art processes.
In the past, those skilled in the art attempted to minimize such motion artifacts by various breathing gating or triggering schemes. A serious drawback in the use of gating schemes, among other things, is that respiratory gating or triggering requires additional sophisticated and expensive equipment to generate gating signals and also requires appreciably longer data acquisition time periods with consequent reduced throughput.
More particularly, respiratory triggering comprises waiting with an encoding pulse train until the selected thoraxic position occurs. This means that there is no exact repetition time TR, but rather the repetition is controlled by the breathing. In gating TR=C (a constant)--all portions of the breathing cycle outside of a "window" are rejected. Gating and triggering thus inherently limit the user, as TR is an important factor effecting image quality. Its control is usually left to the user as a tool in selecting the type of contrast desired. In gating, TR is a few seconds instead of the usual TR time of under a second, causing the gated study to last much longer than a non-gated study.
More recently, methods have been used which allow the user to fix TR, but couple the encoding pulse's amplitude to the thoraxic position instead of linearly increasing the amplitude at each pulse repetion as is the usual procedure. See for example, the technical note entitled "Respiratorily Ordered Phase Encoding (ROPE): A Method for Reducing Motion Artifacts in MR Imaging" by D. R. Bailes et al, pp 835-838, Journal of Computer Assisted Tomography, vol. 9,(4) July/August 1985; U.S. Pat. Nos. 4,564,017 and 4,567,893.
A popular method makes the encoding amplitude a monotonic function of the thoraxic position. Thus, in theory after reordering the encoding pulse amplitude, most of the effects of the breathing frequency are eliminated. In fact, what this does is change the quasi-cyclic nature of the breathing into a quasi-linear function or a slowly changing function.
Making the encoding pulse amplitude a simple function (say linear) of the thoraxic position introduces new problems. Some positions are more likely to occur than others, and will probably repeat before the less likely positions occur the first time. This wastes time whatever is done with the redundant data obtained because of the repetitions (the redundant data can be discarded, averaged with the previous data from the same amplitude, etc.). Since the time to repeat and the breathing frequency are not synchronized some breathing cycle positions will occur a second or a third time before others have occured once. This happens because the breathing cycle position is "random" relative to the occurence of the encoding pulses and also because during the breathing cycles there are sections with relatively slow motion and others with relatively fast motion. The position axis values that are traversed during the part of the cycle where the motion is slow are more likely to be detected in a random sampling arrangement than the position axis values traversed where the motion is fast; partially because the slower motion part of the breathing cycle extends over a longer time period.
Another solution tried has been the use of the integral of the temporal probability function of the thoraxic position as the mapping function for position vs. encoding pulse amplitude. This creates a flat, nearly constant probability function for the encoding amplitudes. However, as the thoraxic position is a function of the breathing process and is independant of TR, the position is random relative to the pulse train number. The statistical nature of the sampling will, therefore, cause some positions to repeat numerous times before other positions occur even once. Thus, this solution is also not sufficiently efficient.
In one particular prior art method used to speed up the process of activating all of the required encoding pulses, the encoding pulse amplitudes per pulse repetition are selected using "bins" instead of varying the amplitude of each ensuing encoding pulse as a direct function of the thoraxic or breathing cycle. Each bin is defined by a range of respiratory cycle positions. A range of encoding pulse amplitudes is assigned to each bin. Each received breathing cycle position then determines a bin and the next encoding pulse amplitude is selected from the determined bin.
There may be different methods of selecting the encoding pulse amplitude once the bin is selected. For example, the central amplitude allocated to the bin may be the amplitude of first choice when the breathing cycle position first indicates a particular bin. At the second indication of the particular bin, the first amplitude greater than the central amplitude is selected. The third indication of the particular bin selects the encoding pulse amplitude immediately less than the central amplitude. This process continues until all of the encoding pulse amplitudes assigned to each of the particular bins are used.
The bin methods also increase the data acquisition time. For example, if each bin includes only one encoding amplitude; then if a breathing cycle position is sampled which has already been sampled, (double sampling) the immediate reaction is to skip it. A few sequences of the data could perhaps be skipped without serious loss. However, as more and more encoding amplitudes are used it becomes increasingly more probable that the next sampled position of the breathing cycle will be a double sampling. The probability of sampling a previously unsampled breathing position decreases with time both because less sample positions are left and because the more probable positions are usually sampled earlier. The last few encoding amplitudes may therefore require a large number of "aborted" samplings and a very long marginal time to obtain. Larger bins alleviate the problem of cancellation but fail to eliminate the problem of motion artifacts.
Use of different, more complicated binning methods may indeed decrease the acquisition time but only partially solve the problem of the artifacts. Consider that the sampling of the breathing cycle position is random relative to the encoding pulse time, therefore, statistically one of the bins will always be used up first, because this bin has a higher probability of utilization and therefore will be double sampled with a consequent waste of time.
Still another problem with the binning solutions is that such solutions assume a constant unchanging breathing cycle. In practice breathing cycles tend to vary in amplitude, time and shape. For example, the amplitude may decrease, thereby eliminating the sampling of certain positions and consequently creating the possibility of corresponding bins not being used entirely or only being partially used. Attempted solutions to the problems raised by varying breathing cycles include limiting the transformation function to a region smaller than that indicated by the breathing amplitude as determined preliminarily and using bins of equal probability rather than bins of equal intervals.
Limiting the transformation function to a region smaller than the breathing cycle tends to erase part of the breathing cycle. Using bins of equal probability suffers because breathing cycle position probabilities also change with variations in the breathing cycles and the bin sizes are therefore no longer are optimal.